Closed qkrtnskfk23 closed 1 year ago
Could you please provide you fine-tuning command and host-demo command?
I use --quant and --only_save_trainable for multi-turn training based on shared_gpt format.
For fine-tuning,
python demos/multi_turn.py \ --llama_config llama/llama-2-7b/params.json --tokenizer_path /llama/tokenizer.model --pretrained_path /llama/llama-2-7b
For demo, python demos/multi_turn.py \ --llama_config llama/llama-2-7b/params.json --tokenizer_path /llama/tokenizer.model \ --pretrained_path /llama2/output_dir/finetune/sg/dialog_sharegpt/epoch3
Thanks.
For demo, it is required to pass both base weights and trainable weights to --pretrained_path
.
In your case, it should be like:
python demos/multi_turn.py \
--llama_config llama/llama-2-7b/params.json \
--tokenizer_path /llama/tokenizer.model \
--pretrained_path <path/to/llama-2-7b> /llama2/output_dir/finetune/sg/dialog_sharegpt/epoch3 \
--quant \
--llama_type <choose llama type>
It is important to choose the correct --llama_type
:
(1) if the model is finetuned under normBias setting, please use --llama_type llama_peft
(2) if the model is finetuned under normBiasLora setting, please use --llama_type llama_peft
and --llama_config llama/llama-2-7b/params.json configs/model/finetune/sg/llamaPeft_normBiasLora.json
It works! Thank you!!
Hi,
I conducted fine-tuning of lamma2 on my own dataset.
However, the results of fine-tuned model is really weird.
Response: triggertriggertriggertriggertriggertriggertriggertriggertriggertriggertriggertriggertrigger.....
Do you know any solution or any causation of this issue?
Additionally, the closs is monotonically decreased from 1.5 to 0.3 for 4 epochs.
Thanks